Dynamical Systems

Complex systems are pervasive in many areas of science integrated in our daily lives. Examples include financial markets, highway transportation networks, telecommunication networks, world and country economies, social networks, immunological systems, living organisms, computational systems and electrical and mechanical structures. Complex systems are often composed of a large number of interconnected and interacting entities, exhibiting much richer global scale dynamics than the properties and behavior of individual entities. Complex systems are studied in many areas of natural sciences, social sciences, engineering and mathematical sciences. This special issue therefore intends to contribute towards the dissemination of the multifaceted concepts in accepted use by the scientific community. We hope readers enjoy this pertinent selection of papers which represents relevant examples of the state of the art in present day research. [...

Computational Design of Synthetic Microbial Communities

In naturally occurring microbial systems, species rarely exist in isolation. There is strong ecological evidence for a positive relationship between species diversity and the functional output of communities. The pervasiveness of these communities in nature highlights that there may be advantages for engineered strains to exist in cocultures as well. Building synthetic microbial communities allows us to create distributed systems that mitigate issues often found in engineering a monoculture, especially when functional complexity is increasing. The establishment of synthetic microbial communities is a major challenge we must overcome in order to implement coordinated multicellular systems. Here I present computational tools that help us design engineering strategies for establishing synthetic microbial communities. Using these tools I identify promising candidates for several design scenarios. This work highlights the importance of parameter inference and model selection to build robust communities. The findings highlight important interaction motifs that provide stability, and identify requirements for selecting genetic parts and tuning the community composition. Additionally, I show that fundamental interactions in small synthetic communities can produce chaotic behaviour that is unforecastable. Together these findings have important ramifications for how we build synthetic communities in the lab, and the considerations of interactions in microbiomes we manipulate

Measuring and modelling the energy demand reduction potential of using zonal space heating control in a UK home

Most existing houses in the UK have a single thermostat, a timer and conventional thermostatic radiator valves to control the low pressure, hot water space heating system. A number of companies are now offering a solution for room-by-room temperature and time control in such older houses. These systems comprise of motorised radiator valves with inbuilt thermostats and time control. There is currently no evidence of any rigorous scientific study to support the energy saving claims of these zonal control systems. This thesis quantifies the potential savings of zonal control for a typical UK home. There were three components to the research. Firstly, full-scale experiments were undertaken in a matched pair of instrumented, three bedroom, un-furbished, 1930s, test houses that included equipment to replicate the impacts of an occupant family. Secondly, a dynamic thermal model of the same houses, with the same occupancy pattern, that was calibrated against the measured results. Thirdly, the experimental and model results were assessed to explore how the energy savings might vary in different UK climates or in houses with different levels of insulation. The results of the experiments indicated that over an 8-week winter period, the house with zonal control used 12% less gas for space heating compared with a conventionally controlled system. This was despite the zonal control system resulting in a 2 percentage point lower boiler efficiency. A calibrated dynamic thermal model was able to predict the energy use, indoor air temperatures and energy savings to a reasonable level of accuracy. Wider scale evaluation showed that the annual gas savings for similar houses in different regions of the UK would be between 10 and 14% but the energy savings in better insulated homes would be lower